Affiliation:
1. Department of Informatics and Computer Engineering, University of West Attica, Athens, Greece
Abstract
The classification of works of art in terms of artistic style is a complex task. Some painting styles are closely related to the form of their brushstrokes. Salient examples are Pointillism and Impressionism, having both distinguishable brushstroke characteristics which are small, rounded of clear color, repetitive dots for Pointillism style and visible, elongated and slanting, repetitive touches for Impressionism style. As Impressionism is the ancestral style of Pointillism, the two styles have many elements in common and distinguishing them is difficult. In this article, specific texture features are investigated for the classification of the two styles, focusing mainly on small differences in their brushstrokes. The texture features adopted are Granulometric features, gray-level co-occurrence matrix features, and run length features. It is shown experimentally that the run length method outperforms the other features and can efficiently (up to 95%) discriminate the two textured styles since it incorporates information about size, direction, and intensity of brushstrokes.
Publisher
Association for Computing Machinery (ACM)
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